The Future of RAG: Exploring Advanced LLM Architectures with LangChain and Redis

Simplify RAG development for AI apps with LangChain and Redis.

Watch this session for an in-depth exploration of Retrieval-Augmented Generation (RAG) and its application within the LangChain framework. RAG is a key technique for integrating domain-specific data with Large Language Models (LLMs) that is crucial for organizations looking to unlock the power of LLMs.

This session will highlight LangChain’s role in facilitating RAG-based applications, advanced techniques, and the critical role of Redis Enterprise in enhancing these systems’ adaptability, resiliency, and performance at scale.

Watch this session to gain insight into:

• The purpose and value of RAG
• The evolution of RAG systems from basic to modern techniques that can handle diverse data types and business needs
• Practical examples illustrating the power of LangChain and Redis in RAG architectures